With the growth of the human population comes the constantly rising demand for agricultural products. Nevertheless, as the world experiences climate change, many crops are often damaged by weather conditions.This study utilizes Intelligent Agriculture IoT equipment to monitor the environmental factors on a farm. The collected data underwent 3D cluster analysis to yield analysis of the environmental factors of that farm. The proposed scheme bears the following features: (1) data normalization is achieved via the combination of moving average and average variance; (2) we applied 3D cluster analysis to analyze the relation between environmental factors and subsequently examine the rules of thumb held by the farmers; (3) the system determines whether a selected crop has been placed in the appropriate cluster; and (4) the system sets a critical value in the cluster based on future environments and provides advice on whether a crop is suitable for the farm. We placed Intelligent Agriculture IoT equipment in the farm for monitoring purposes and ran an actual-scenario analysis using the algorithm in our study; results confirm that our proposed scheme is indeed feasible.

The Internet of Vehicle (IoV) utilizes networks to conduct message exchange and related services or application. In recent years, smart cities and IoVs have become areas of interest in the new generation Internet of Things development, especially since the development of intelligent transportation system has focused on bettering traffic conditions. This paper proposes establishing an intelligent transportation system with a network security mechanism in an IoV environment, with emphasis on the following aspects: 1) this paper integrates intelligent transportation systems in traffic signal control to aid emergency vehicles in more promptly arriving at its destination; 2) in the case of traffic incidents, this paper's approach allows regular vehicles to obtain proof of incident from pertaining authorities and learn about nearby vehicles global positioning system information, such as position and speed, and utilize their car camcorder data for proving purposes; and 3) this paper combines roadside units (RSUs) with traffic signal control and transmits important information to the certificate authority (CA) for storage. Given that RSUs are limited in computation ability and storage space, we can assess and filter the information before sending it to the CA, reducing RSUs computational burden and storage space usage. This paper satisfies IoVs network security requirements of authentication, non-repudiation, conditional anonymity, and conditional untraceability, and, as seen from experiment results, the proposed method is superior to that of other studies.

This paper proposes building a sustainable development computing system for large organizations based on AI and IoT. The system leverages AI to calculate the carbon emissions caused by large organizations' activities and utilizes IoT devices to monitor and compute environmental coefficients. The system also employs automated devices to achieve net-zero carbon emissions. By integrating weather forecast information from meteorological agencies to understand external environmental conditions, and by consulting a knowledge database to devise appropriate response strategies, the AI system can activate relevant equipment to improve both the organization's living environment and carbon emission processes. The feasibility and practical application of this system will be demonstrated through actual simulations to enhance its viability and effectiveness.

The sustainable utilization of marine resources is a vital issue to enrich marine life and to prevent species extinction caused by overfishing. Nowadays, it is common that commercial and smaller vessels are equipped with an Automatic Identification System (AIS) and GPS for better vessel tracking to avoid vessel collision as well as mayday calls. Additionally, governments can monitor vessels’ sea activities through AIS messages, stopping them from overfishing or tracking if any vessel has caused marine pollution. However, because AIS devices cannot guarantee data security, they are susceptible to malicious attacks such as message modification or an illegitimate identity faking a distress signal that causes other vessels to change their course. Given the above, a comprehensive network security system of a sustainable marine environment should be proposed to ensure secure communication. In this paper, a stationary IoT-enabled (Internet of Things) vessel tracking system of a sustainable marine environment is proposed. The system combines network security, edge computing, and tracking management. It offers the following functions: (1) The IoT-based vessel tracking system tracks each aquafarmer’s farming zone and issues periodic warning to prevent vessel collision for pursuing a sustainable marine environment; (2) the system can serve as a relay station that evaluates whether a vessel’s AIS data is correct; (3) the system detects abnormal behavior and any irregular information to law enforcement; (4) the system’s network security mechanism adopts a group key approach to ensure secure communication between vessels; and (5) the proposed edge computing mechanism enables the tracking system to perform message authentication and analysis, and to reduce computational burden for the remote or cloud server. Experiment results indicate that our proposed system is feasible, secure, and sustainable for the marine environment, and the tendered network security mechanism can reduce the computational burden while still ensuring security.